ADU Data from LA Data Portal

LA Times Neighborhoods Data

Create a two layer map

Spatial Join

Map Neighborhoods by ADU Count

Make Interactive ADU Map

To do so we will use plotly express. Since we projected our data to web mercator, note that we have to project it back to WGS84 to work with plotly.

Get the center lat/lon to Map

Plotly maps requires you to give it center coordinates. Let's calculate this based on the data.

ADU Spatial Analysis

Spatial Analysis Methodology

Map the census block groups

Subplots for Multi-Layer Maps

Subplots allows the creation of multiple plots on a gridded canvas. For our map, we only need a single subplot, but we are layering multiple datasets on top of one another on that subplot (block groups and ADU permit data in this instance). To specify which subplot to put the layer on, you use the ax argument.

Spatial Join (again)

Normalize the Data (ADUs per 1000 People)

New Choropleth Map of ADUs with Normalized Data

So far we have imported two datasets (ADU permits and Census Block Groups) and mapped them to show the location of ADUs per 1000 people by census block groups. The resulting map demonstrates spatial clusters of where ADU permits are being issued more frequently, but to what degree of certainty can we say so?

Global Spatial Autocorrelation

Global Moran's I Statistic

Spatial Lag

Side by Side Maps

We now have a spatial lag map: a map that displays geographies weighted against the values of its neighbors. The clusters are much clearer and cleaner than the original ADU count map.

Moran's Plot

Local Spatial Autocorrelation

In the scatterplot above, the colored dots represents the rows that have a P-value less that 0.05 in each quadrant. In other words, these are the statisticaly significantly, spatially autocorrelated geographies.

Spatial Autocorrelation Map

Interactive LISA Map

Hotspot Map

Map Interpretation